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Synthetic data generation has drawn growing attention due to the lack of training data in many application domains. It is useful for privacy-concerned applications, e.g. digital health applications based on electronic medical records. It is also attractive for novel applications, e.g. multimodal...
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Duration: 3.5-year fixed-term appointment Remuneration: The successful applicant will receive a tax-free stipend of $37,145 per annum (2026 full-time rate), as per the Monash Research Training Program (RTP
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through the education faculty peer mentoring program. I do not take for granted the opportunities that I have been able to pursue thanks to the increased financial stability my scholarship has provided. Am
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-task, we encourage you to apply. General Practice experience and intermediate to advance computer skills are desirable, but not essential. A valid driver’s license and willingness to drive to general
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. Participating in an overseas study program . This excludes the Global Immersion Guarantee. Living with a disability or medical condition. You must be registered with Disability Support Services . Benefits $3,000
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students entering the Bachelor of Commerce (Honours) program majoring in Marketing at Monash University. This scholarship provides financial support to full-time students, awarded on the basis of academic
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for computational analysis. This learning analytics project will be conducted in the context of simulation-based healthcare education, and it will support the development of effective strategies to improve teamwork
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My research focuses on the dramatic final stages of massive stars, exploring how they end their lives as gamma-ray bursts, supernovae, and kilonovae. To unravel these mysteries, I employ a combination of multi-wavelength observational data with sophisticated simulations. I am a member of various...
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You must meet the following criteria: Hold or about to complete an undergraduate degree or equivalent qualification recognised for admission to the Monash Juris Doctor Program. Intend to enrol
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Many machine learning (ML) approaches have been applied to biomedical data but without substantial applications due to the poor interpretability of models. Although ML approaches have shown promising results in building prediction models, they are typically data-centric, lack context, and work...